Laparoscopic liver surgery is complicated due to the structure of this organ with open sinusoids. A serious disadvantage is the risk of gas embolism (GE) due to CO2 pneumoperitoneum. CO2 can enter the vascular system through a wounded vein. A common opinion is that gas fluxes along a pressure gradient, e.g. CVP-intra abdominal pressure (IAP). The occurrence of GE could also be eased by entrainment, a ‘Venturi-like’ effect, due to cyclic differences in thoracic pressure and blood flow caused by mechanical ventilation at normal frequency. The aims of these studies were to survey, in a porcine model, the influence on respiratory and haemodynamic variables by GE, to determine at what frequency, severity and duration GE occurs during laparoscopic liver resection (LLR) and whether there are methods to influence the occurrence or severity of GE. Pulmonary and circulatory variables were monitored and measured as well as continuous blood gas monitoring. Transoesophageal echocardiogram was used to identify GE and, according to the amount of bubbles in the right outflow tract of the heart, GE was graded as 0, 1 and 2. Pneumoperitoneum was created by using CO2and IAP was set to 16 mm Hg. A single bolus dose of CO2 influenced respiratory and haemodynamic variables for at least 4 h. During LLR GE occurred in 65-70% of the animals, of which the more serious caused negative influence on cardiopulmonary variables. Elevated PEEP (15 cm H2O) increased CVP but GE occurred irrespective if CVP was lower than or exceeded IAP. In two last studies, a hepatic vein was cut and left open for 3 m before it was clipped. Interestingly, no signs of GE were seen despite an open vein and IAP > CVP in 8 of 20 animals. In the last study high frequency jet ventilation was used in order to minimise the risk of entrainment. The duration of GE was shortened. The occurrence of GE seemed to be influenced by several different factors. The physiological reaction of a GE is impossible to predict for a specific patient, and depends among other factors on comorbidity, and amount, site and entrance rate of GE.

This volume contains four essays on various topics in the field of financial econometrics. All four discuss the properties of high frequency financial data and its implications on the model choice when an estimate of the capital asset return volatility is in focus. The interest lies both in characterizing "stylized facts" in such series with time series models and in predicting volatility. The first essay, entitled A Survey of Recent Papers Considering the Standard &amp; Poor 500 Composite Stock Index, presents recent empirical findings and stylized facts in the financial market from 1987 to 1996 and gives a brief introduction to the research field of capital asset return volatitlity models and properties of high frequency financial data. As the title indicates, the survey is restricted to research on the well known Standard &amp; Poor 500 index. The second essay, with the title, Stylized Facts of Daily Return Series and the Hidden Markov Model, investigates the properties of the hidden Markov Model, HMM, and its capability of reproducing stylized facts of financial high frequency data. The third essay, Modelling the Conditional Mean and Conditional Variance: A combined Smooth Transition and Hidden Markov Approach with an Application to High Frequency Series, investigates the consequences of combining a nonlinear parameterized conditional mean with an HMM for the conditional variance when characterization of stylized facts is considered. Finally, the fourth essay entitled, Volatility Forecasting for Option Pricing on Exchange Rates and Stock Prices, investigates the volatility forecasting performance of some of the most frequently used capital asset return volatility models such as the GARCH with normal and t-distributed errors, the EGARCH and the HMM. The prediction error minimization approach is also investigated. Each essay is self-contained and could, in principle, be read in any order chosen by the reader. This, however, requires a working knowledge of the properties of the HMM. For readers less familiar with the research field the first essay may serve as an helpful introduction to the following three essays. / <p>Diss. Stockholm : Handelshögsk.</p>

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Estimating the integrated volatility of high frequency realized prices is an important issue in microstructure literature. Bandi and Russell (2006) derived the optimal-sampling frequency, and Zhang et al. (2005) proposed a "two-scales estimator" to solve the problem. In this study, we propose a new estimator based on a signal to noise ratio statistic with convergence rate of Op (n^(−1/ 4) ). The method is applicable to both constant and stochastic volatility models and modi¡Âes the Op (n^(−1/ 6) ) convergence rate of Zhang et al. (2005). The proposed estimator is shown to be asymptotic e¡Ócient as the maximum likelihood estimate for the constant volatility case. Furthermore, unbiased estimators of the two elements, the variance of the microstructure noise and the fourth moment of the realized log returns, are also proposed to facilitate the estimation of integrated volatility. The asymptotic prop- erties and e&#x00AE;ectiveness of the proposed estimators are investigated both theoretically and via simulation study.

Magnetic components, such as inductors and transformers, have important effects on the efficiency and performance of switching power supplies; their parasitic properties directly impact the high frequency properties which can cause lot-to-lot variation or unanticipated and non-ideal operation. They are also amongst the most problematic components to design, often requiring numerous design-prototype-test interactions. The electrostatic and electromagnetic analysis of wound components has become more important recently to predict their performance and frequency behavior. Accurate prediction and design of winding parasitic parameters of leakage inductance and winding capacitance for high frequency inductors and transformers in switching power supplies is fundamental to improve performance, lower cost, and speed time to market. This thesis presents a methodology and process to obtain accurate prediction of the inter- and intra-winding capacitances of high frequency magnetic components. Application examples considered are a single-winding choke, a coupled inductor filter, and a multi-winding transformer. Analytical approach for determination of parasitic capacitances in high frequency magnetic components will be covered also. Comparison of the FEA results using JMAG with experimental and empirical formula results show good agreement, supporting the method as a model-based design tool with the potential to significantly reduce the design-prototype-test cycle commonly needed with sophisticated magnetic designs.

The main focus of this thesis is on fast numerical methods, where adaptivity is an important mechanism to lowering the methods' complexity. The application of the methods are in the areas of wireless communication, antenna design, radar signature computation, noise prediction, medical ultrasonography, crystal growth, flame propagation, wave propagation, seismology, geometrical optics and image processing.   We first consider high frequency wave propagation problems with a variable speed function in one dimension, modeled by the Helmholtz equation. One significant difficulty of standard numerical methods for such problems is that the wave length is very short compared to the computational domain and many discretization points are needed to resolve the solution. The computational cost, thus grows algebraically with the frequency w. For scattering problems with impenetrable scatterer in homogeneous media, new methods have recently been derived with a provably lower cost in terms of w. In this thesis, we suggest and analyze a fast numerical method for the one dimensional Helmholtz equation with variable speed function (variable media) that is based on wave-splitting. The Helmholtz equation is split into two one-way wave equations which are then solved iteratively for a given tolerance. We show rigorously that the algorithm is convergent, and that the computational cost depends only weakly on the frequency for fixed accuracy.  We next consider interface tracking problems where the interface moves by a velocity field that does not depend on the interface itself. We derive fast adaptive  numerical methods for such problems. Adaptivity makes methods robust in the sense that they can handle a large class of problems, including problems with expanding interface and problems where the interface has corners. They are based on a multiresolution representation of the interface, i.e. the interface is represented hierarchically by wavelet vectors corresponding to increasingly detailed meshes. The complexity of standard numerical methods for interface tracking, where the interface is described by marker points, is O(N/dt), where N is the number of marker points on the interface and dt is the time step. The methods that we develop in this thesis have O(dt^(-1)log N) computational cost for the same order of accuracy in dt. In the adaptive version, the cost is O(tol^(-1/p)log N), where tol is some given tolerance and p is the order of the numerical method for ordinary differential equations that is used for time advection of the interface.   Finally, we consider time-dependent Hamilton-Jacobi equations with convex Hamiltonians. We suggest a numerical method that is computationally efficient and accurate. It is based on a reformulation of the equation as a front tracking problem, which is solved with the fast interface tracking methods together with a post-processing step.  The complexity of standard numerical methods for such problems is O(dt^(-(d+1))) in d dimensions, where dt is the time step. The complexity of our method is reduced to O(dt^(-d)|log dt|) or even to O(dt^(-d)). / <p>QC 20121116</p>

An emerging non-pharmacological treatment for bone degenerative diseases is whole body vibration (WBV), a mechanical signal composed of low-magnitude, high-frequency (LMHF) vibrations that when applied to bone, have osteogenic and anti-resorptive effects. Currently, the cellular and molecular mechanism underlying the effect of WBV on bone is unclear. In this study, we investigated the response of osteocytes, the putative mechanosensor in bone, under LMHF vibration. As bone cells differentiate from mesenchymal stromal cells (MSCs), we also studied the osteogenic differentiation of rat MSCs in the presence of vibration loading. We found that vibrated osteocytes show gene and protein expression changes suggestive of an anti-osteoclastogenic response, and secrete soluble factors that inhibit osteoclast formation and activity. In contrast, rat MSCs showed moderate to no response to LMHF vibration during osteogenic differentiation. Our data suggest that in vivo effects of LMHF vibration are mediated through mechanosensing and biochemical responses by osteocytes.

An emerging non-pharmacological treatment for bone degenerative diseases is whole body vibration (WBV), a mechanical signal composed of low-magnitude, high-frequency (LMHF) vibrations that when applied to bone, have osteogenic and anti-resorptive effects. Currently, the cellular and molecular mechanism underlying the effect of WBV on bone is unclear. In this study, we investigated the response of osteocytes, the putative mechanosensor in bone, under LMHF vibration. As bone cells differentiate from mesenchymal stromal cells (MSCs), we also studied the osteogenic differentiation of rat MSCs in the presence of vibration loading. We found that vibrated osteocytes show gene and protein expression changes suggestive of an anti-osteoclastogenic response, and secrete soluble factors that inhibit osteoclast formation and activity. In contrast, rat MSCs showed moderate to no response to LMHF vibration during osteogenic differentiation. Our data suggest that in vivo effects of LMHF vibration are mediated through mechanosensing and biochemical responses by osteocytes.

El diseño de modelos equivalentes es una técnica utilizada para llegar a entender el comportamiento de dispositivos trabajando a AAFF. La presente tesis aborda este tema aplicado al transformador. Se han recopilado y analizado los trabajos más relevantes referidos al modelado del transformador en alta frecuencia. Tomando como base experimental un transformador trifásico de 4 kVA, se han planteado los montajes y metodologías asociadas para conseguir los modelos de baja y alta frecuencia. Los modelos obtenidos pueden ser sintetizados a circuitos RLC y su precisión evaluada mediante sencillos montajes. Inicialmente, se somete a prueba al modelo clásico de BF para determinar la frecuencia máxima hasta la que puede ser utilizado. A continuación, se propone un nuevo modelo en AF y su respuesta es evaluada y validada mediante medidas. / Modelling is a useful technique able to provide a suitable knowledge about the behaviour of all the devices operated at high frequencies. This thesis approaches this topic to the case of the transformer. A state of the art about high-frequency modelling is summarized and the most relevant research works are analysed. By using a 4 kVA three-phase power transformer, a set-up facility and the associated methodology has been proposed in order to develop a method able to obtain both the low and high-frequency models. The obtained model can be synthesized using passive LCR circuits. The accuracy of the model is then evaluated using the set-up facility. In initial experiments, the classic low-frequency model is put to the test in order know the maximum frequency at which the model can be used. After that, a new high-frequency model is proposed and its response is evaluated and validated with measurements.

In this paper we use model-free estimates of daily exchange rate volatilities employing high-frequency intraday data, known as Realized Volatility, which is then forecasted with ARMA-models and used to produce one-day-ahead Value-at-Risk predictions. The forecasting accuracy of the method is contrasted against the more widely used ARCH-models based on daily squared returns. Our results indicate that the ARCH-models tend to underestimate the Value-at-Risk in foreign exchange markets compared to models using Realized Volatility